## PYTHON PROJECTS

## Handwritten character recognition using python opencv

Hand written character recognition is much evolving technique. In this work, dataset is trained with SVM model. Capital Letters and Small letters of Alphabets are recognized suing opencv. Python Demo

## Real Estate Price prediction Regression, Lasso, SVM, Decision Tree

Real Estate Price prediction Regression, Lasso, SVM, Decision Tree Python Demo

## Cricket match result prediction using Decision Tree, SVM, Naive Bayes, Logistics Regression

Cricket match result prediction using four ML algorithms Decision Tree, SVM, Naive Bayes, Logistics Regression Python demo

## Rainfall prediction using Lasso and Decision Tree alogrithm on Python

Implementation Details: ———————– We are taking dataset X Train & Test is from ID to Oct-Dec (NOT ANNUAL Column) Y Train & Test is the Annual column We are taking dataset and Analysing dataset & plotted all graphs. Using Train set of X & Y we are applying ML algorithm Lasso and Decision Tree For X testset, we are arriving results and stored as resultLasso & resultDecisionTree Python Demo

## k means++ Cluster algorithm for Heart Disease prediction

k means++ Cluster algorithm for Heart Disease prediction Implementation Details: ———————– Heart Disease Prediction using K-Means and K-means++ clustering and Logistics Regression 1. We are taken dataset data.csv 2. Input data.csv is split into three cluster by K-means algorithm taking centroid automatically. Whereas k-means++ arrives centroid with distance Cluster 0, Cluster1, Cluster2 3. Every cluster data is taken for getting trainset and test set Trainset contains 14 columns, whereas testset contains 13 column 4. Every cluster testset is predicted for heart disease Accuracy is arrived 5. Logistics regression is performed…

## Personality Prediction in Tweets

PERSONALITY PREDICTION FROM TWEETS Implementation Details: ———————– 1. Twitter data is collected for topic “apple” and stored as twitter.json file. The data will be added in the same file for execution of Twitterdata.py 2. Collected tweets from json file is extracted stored as tweet.csv data extracted from each tweet are tweet_id tweet_time tweet_author tweet_author_id tweet_language tweet_text polarity tweet_sentiment More 1000 tweets are collected 3. Naive Bayes and Logistics regression are applied, Plots are arrived For the taken dataset, x-train and x-test and y-train & y-test are arrived. from which te…

## Twitter sentiment analysis using five machine learning techniques

Twitter Sentiment Analysis using 5 Machine learning Techniques Implementation Details: ———————– 1. Twitter data is collected for topic “apple” and stored as twitter.json file. The data will be added in the same file for execution of Twitterdata.py 2. Collected tweets from json file is extracted stored as tweet.csv data extracted from each tweet are tweet_id tweet_time tweet_author tweet_author_id tweet_language tweet_text polarity tweet_sentiment More 1000 tweets are collected 3. 5 machine learning techniques were applied 1.Naive Bayes 2.Logistics regression 3.SVM technique 4.Random forest and 5.K-means Clustering Plots are arrived For the…

## Restaurant Recommendation using collaborative Filtering

Restaurant Recommendation using collaborative Filtering We are extracting real time data from Yelp Dataset.csv is extracted Collaborative filtering is used for recommendation results Python Demo

## Students Result Prediction and Analysis with alcohol consumption dataset

Students Result Prediction and Analysis with alcohol consumption dataset This project is implemented for student grade prediction, who consume daily alcohol and weekly alcohol. Algorithm used : SVM and K-means algorithm, both implemented and compared Python Demo

## Real Estate Price Prediction using Lasso algorithm and Logistics Regression

Real Estate Price Prediction using Lasso algorithm and Logistics Regression Python Demo